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Using apparent density of paper from hardwood kraft pulps to predict sheet properties, based on unsupervised classification and multivariable regression techniques

2015Journal article Open access
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dc.contributor.authorAnjos, O.
dc.contributor.authorGarcía-Gonzalo, Esperanza
dc.contributor.authorSantos, António J.
dc.contributor.authorSimões, Rogério
dc.contributor.authorMartínez-Torres, Javier
dc.contributor.authorPereira, Helena
dc.contributor.authorGarcía-Nieto, Paulino
dc.date.accessioned2015-08-03T17:09:38Z
dc.date.available2015-08-03T17:09:38Z
dc.date.issued2015
dc.description.abstractPaper properties determine the product application potential and depend on the raw material, pulping conditions,and pulp refining. The aim of this study was to construct mathematical models that predict quantitative relations between the paper density and various mechanical and optical properties of the paper. A dataset of properties of paper handsheets produced with pulps of Acacia dealbata, Acacia melanoxylon, and Eucalyptus globullus beaten at 500, 2500, and 4500 revolutions was used. Unsupervised classification techniques were combined to assess the need to perform separated prediction models for each species, and multivariable regression techniques were used to establish such prediction models. It was possible to develop models with a high goodness of fit using paper density as the independent variable (or predictor) for all variables except tear index and zero-span tensile strength, both dry and wet.por
dc.identifier.citationANJOS, O. [et al.] (2015) - Using apparent density of paper from hardwood kraft pulps to predict sheet properties, based on unsupervised classification and multivariable regression techniques. Bioresources. 10:3. p. 5920-5931.por
dc.identifier.doi10.15376/biores.10.3.5920-5931
dc.identifier.urihttp://hdl.handle.net/10400.11/2942
dc.language.isoporpor
dc.peerreviewedyespor
dc.relation.publisherversionhttp://ojs.cnr.ncsu.edu/index.php/BioRespor
dc.subjectUnsupervised classificationpor
dc.subjectMultivariable regressionpor
dc.subjectPaperpor
dc.subjectAcacia dealbatapor
dc.subjectAcacia melanoxylonpor
dc.subjectEucalyptus globuluspor
dc.titleUsing apparent density of paper from hardwood kraft pulps to predict sheet properties, based on unsupervised classification and multivariable regression techniquespor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage5931por
oaire.citation.startPage5920por
oaire.citation.titleBioresourcespor
oaire.citation.volume10(3)por
person.familyNameAnjos
person.givenNameOfélia
person.identifier.ciencia-idC21D-D8C7-3037
person.identifier.orcid0000-0003-0267-3252
person.identifier.ridG-2808-2012
person.identifier.scopus-author-id23395659700
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublicationdf9191ae-0bbb-4bb8-bbdc-0f79c7365876
relation.isAuthorOfPublication.latestForDiscoverydf9191ae-0bbb-4bb8-bbdc-0f79c7365876

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